TY - JOUR
T1 - Adaptive swarm optimization for locating and tracking multiple targets
AU - Liu, Jun
AU - Ren, Xuemei
AU - Ma, Hongbin
PY - 2012/11
Y1 - 2012/11
N2 - Locating and tracking multiple targets in the dynamic and uncertain environment is a crucial and challenging problem in many practical applications. The main task of this paper is to investigate three fundamental problems, which are composed of the identification of irregular target, locating multiple targets and tracking multiple targets. Firstly, the proposed objective function successfully gets the target's shape to discern eccentric target in the specific environment. Secondly, for the sake of locating multiple targets, the adaptive PSO algorithm divides the swarm into many subgroups, and adaptively adjusts the number of particles in each subgroup by the competition and cooperation technology. Thirdly, in order to track multiple targets in the dynamic environment, the proposed swarm optimization has the characteristic of the adaptively covered radius of the subgroup according to the minimum distance among other subgroups. To show the efficiency and high performance of the proposed algorithms, several algorithms chiefly concentrate on locating and tracking three ants in the practical systems.
AB - Locating and tracking multiple targets in the dynamic and uncertain environment is a crucial and challenging problem in many practical applications. The main task of this paper is to investigate three fundamental problems, which are composed of the identification of irregular target, locating multiple targets and tracking multiple targets. Firstly, the proposed objective function successfully gets the target's shape to discern eccentric target in the specific environment. Secondly, for the sake of locating multiple targets, the adaptive PSO algorithm divides the swarm into many subgroups, and adaptively adjusts the number of particles in each subgroup by the competition and cooperation technology. Thirdly, in order to track multiple targets in the dynamic environment, the proposed swarm optimization has the characteristic of the adaptively covered radius of the subgroup according to the minimum distance among other subgroups. To show the efficiency and high performance of the proposed algorithms, several algorithms chiefly concentrate on locating and tracking three ants in the practical systems.
KW - Locating
KW - Multiple targets
KW - Particle swarm optimization
KW - Tracking
UR - http://www.scopus.com/inward/record.url?scp=84865863497&partnerID=8YFLogxK
U2 - 10.1016/j.asoc.2012.06.005
DO - 10.1016/j.asoc.2012.06.005
M3 - Article
AN - SCOPUS:84865863497
SN - 1568-4946
VL - 12
SP - 3656
EP - 3670
JO - Applied Soft Computing
JF - Applied Soft Computing
IS - 11
ER -